吉林大学学报(理学版) ›› 2019, Vol. 57 ›› Issue (5): 1179-1184.

• 计算机科学 • 上一篇    下一篇

基于粒子群优化算法的高速网络可变结构节点位置控制

郁诺1, 刘洋2   

  1. 1. 西安财经大学 信息与教育技术中心, 西安 710061; 2. 河南财经政法大学 云计算与大数据研究所, 郑州 450046
  • 收稿日期:2018-12-10 出版日期:2019-09-26 发布日期:2019-09-20
  • 通讯作者: 郁诺 E-mail:xaufe@163.com

Variable Structure Node Position Control of High Speed NetworksBased on Particle Swarm Optimization Algorithm

YU Nuo1, LIU Yang2   

  1. 1. Information & Education Technology Center, Xi’an University of Finance & Economics, Xi’an 710061, China;
    2. Institute of Cloud Computing and Big Data, Henan University of Economics and Law, Zhengzhou 450046, China
  • Received:2018-12-10 Online:2019-09-26 Published:2019-09-20
  • Contact: YU Nuo E-mail:xaufe@163.com

摘要: 针对网络节点位置控制中网络容量较低、 控制过程节点能量消耗较大等问题, 提出一种基于粒子群优化算法的高速网络可变结构节点位置控制方法. 该方法结合粒子群优化算法与Metropolis接受准则, 找到各网络节点对应的粒子位置, 对初始位置权重进行自适应调节, 得出粒子最优值并建立高速网络可变结构节点位置控制模型, 以实现可变结构节点位置控制. 仿真实验与当前方法进行对比测试的结果表明, 该网络节点位置控制方法在250个节点位置控制实验过程中, 能量消耗可控制在30 kJ内, 控制效率较高.

关键词: 高速网络, 节点, 位置, 智能控制

Abstract: Aiming at the problems of low network capacity and large energy consumption of nodes in the control process, we proposed a variable structure node position control method of high speed network based on particle swarm optimization algorithm. The method combined with particle swarm optimization algorithm and Metropolis acceptance criterion, found the corresponding particle positions of each network node, adaptively adjusted the initial position weight, obtained the particle optimal value, and established the position control model of variable structure node of high speed network to realize the position control of variable structure node. The simulation experiments were compared with the current methods, the results show that the energy consumption can be controlled within 30 kJ in the experiment of 250 node position control,  and the control efficiency is high.

Key words: high speed network, node, location, intelligent control

中图分类号: 

  • TP212.9